IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v15y2022i9p3412-d810227.html
   My bibliography  Save this article

Construction Management Supported by BIM and a Business Intelligence Tool

Author

Listed:
  • Fernanda Rodrigues

    (RISCO—Research Center for Risks and Sustainability in Construction, Civil Engineering Department, University of Aveiro, Campus Universitário de Santiago, 3810-193 Aveiro, Portugal)

  • Ana Dinis Alves

    (RISCO—Research Center for Risks and Sustainability in Construction, Civil Engineering Department, University of Aveiro, Campus Universitário de Santiago, 3810-193 Aveiro, Portugal)

  • Raquel Matos

    (RISCO—Research Center for Risks and Sustainability in Construction, Civil Engineering Department, University of Aveiro, Campus Universitário de Santiago, 3810-193 Aveiro, Portugal)

Abstract

The construction sector generates large amounts of heterogeneous and dynamic data characterized by their fragmentation throughout the life cycle of a project. Immediate and accurate access to that data is fundamental to the management, decision-making and analysis by construction owners, supervisors, managers, and technicians involved in the different phases of the project life cycle. However, since construction project data are diverse, dispersed, uncorrelated, and difficult to visualize, a reliable basis for decision-making can rarely be established by the management team. Aiming to bridge this gap, a methodology for data management during building construction by means of Data with BIM and Business Intelligence (BI) analysis tools was developed in this study. This methodology works by extracting data from 3D parametric model and integrating it with a BI tool, through which data are visualized and interrelated with the same database, the BIM model. To demonstrate the applicability of the methodology, a study case was carried out. It was shown that this methodology provides a collaborative platform for accurate data analysis to the construction management and supervision teams, allowing project stakeholders to access and update data in real-time, in permanent linkage with the BIM model. Additionally, improving the reliability of the decision-making process and ensuring project deliverability, the developed methodology contributes to a more sustainable management process by decreasing errors and resource consumption, including energy. Therefore, the main goal of this study is to present a methodology for data analysis with BIM models integrated with BI for sustainable construction management.

Suggested Citation

  • Fernanda Rodrigues & Ana Dinis Alves & Raquel Matos, 2022. "Construction Management Supported by BIM and a Business Intelligence Tool," Energies, MDPI, vol. 15(9), pages 1-14, May.
  • Handle: RePEc:gam:jeners:v:15:y:2022:i:9:p:3412-:d:810227
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/15/9/3412/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/15/9/3412/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Gao, Hao & Koch, Christian & Wu, Yupeng, 2019. "Building information modelling based building energy modelling: A review," Applied Energy, Elsevier, vol. 238(C), pages 320-343.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Mihail Mateev, 2024. "Digital Twins Concept For Energy-Efficient Smart Buildings," Yearbook of the Faculty of Economics and Business Administration, Sofia University, Faculty of Economics and Business Administration, Sofia University St Kliment Ohridski - Bulgaria, vol. 23(1), pages 187-198, June.
    2. Lešnik, Maja & Kravanja, Stojan & Premrov, Miroslav & Žegarac Leskovar, Vesna, 2020. "Optimal design of timber-glass upgrade modules for vertical building extension from the viewpoints of energy efficiency and visual comfort," Applied Energy, Elsevier, vol. 270(C).
    3. Jianwu Xiong & Linlin Chen & Yin Zhang, 2023. "Building Energy Saving for Indoor Cooling and Heating: Mechanism and Comparison on Temperature Difference," Sustainability, MDPI, vol. 15(14), pages 1-20, July.
    4. Sanjin Gumbarević & Ivana Burcar Dunović & Bojan Milovanović & Mergim Gaši, 2020. "Method for Building Information Modeling Supported Project Control of Nearly Zero-Energy Building Delivery," Energies, MDPI, vol. 13(20), pages 1-21, October.
    5. Zhang, Sheng & Liu, Jun & Zhang, Xia & Wang, Fenghao, 2024. "Properly shortening design time scale of medium-deep borehole heat exchanger for high building heating performances with high computational efficiency," Energy, Elsevier, vol. 290(C).
    6. Clyde Zhengdao Li & Yiqian Deng & Yingyi Ya & Vivian W. Y. Tam & Chen Lu, 2023. "Applications of Information Technology in Building Carbon Flow," Sustainability, MDPI, vol. 15(23), pages 1-23, December.
    7. Yu Cao & Liyan Huang & Nur Mardhiyah Aziz & Syahrul Nizam Kamaruzzaman, 2022. "Building Information Modelling (BIM) Capabilities in the Design and Planning of Rural Settlements in China: A Systematic Review," Land, MDPI, vol. 11(10), pages 1-34, October.
    8. Quan Wen & Zhongfu Li & Yifeng Peng & Baorong Guo, 2020. "Assessing the Effectiveness of Building Information Modeling in Developing Green Buildings from a Lifecycle Perspective," Sustainability, MDPI, vol. 12(23), pages 1-20, November.
    9. Jordan Higgins & Aditya Ramnarayan & Roxana Family & Michael Ohadi, 2024. "Analysis of Energy Efficiency Opportunities for a Public Transportation Maintenance Facility—A Case Study," Energies, MDPI, vol. 17(8), pages 1-20, April.
    10. Annamaria Ciccozzi & Tullio de Rubeis & Domenica Paoletti & Dario Ambrosini, 2023. "BIM to BEM for Building Energy Analysis: A Review of Interoperability Strategies," Energies, MDPI, vol. 16(23), pages 1-45, November.
    11. Mohamed Nour El-Din & João Poças Martins & Nuno M. M. Ramos & Pedro F. Pereira, 2024. "The Role of Blockchain-Secured Digital Twins in Promoting Smart Energy Performance-Based Contracts for Buildings," Energies, MDPI, vol. 17(14), pages 1-23, July.
    12. Calama-González, Carmen María & Symonds, Phil & Petrou, Giorgos & Suárez, Rafael & León-Rodríguez, Ángel Luis, 2021. "Bayesian calibration of building energy models for uncertainty analysis through test cells monitoring," Applied Energy, Elsevier, vol. 282(PA).
    13. Ohlsson, K.E. Anders & Olofsson, Thomas, 2021. "Benchmarking the practice of validation and uncertainty analysis of building energy models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 142(C).
    14. Najjar, Mohammad & Figueiredo, Karoline & Hammad, Ahmed W.A. & Haddad, Assed, 2019. "Integrated optimization with building information modeling and life cycle assessment for generating energy efficient buildings," Applied Energy, Elsevier, vol. 250(C), pages 1366-1382.
    15. Gang Yao & Yuan Chen & Wenchi Xie & Nan Chen & Yue Rui & Pingjia Luo, 2022. "Research on Collaborative Design of Performance-Refined Zero Energy Building: A Case Study," Energies, MDPI, vol. 15(19), pages 1-30, September.
    16. Lei Zhang & Zhenwei Chu & Huanbin Song, 2019. "Understanding the Relation between BIM Application Behavior and Sustainable Construction: A Case Study in China," Sustainability, MDPI, vol. 12(1), pages 1-17, December.
    17. Barone, Giovanni & Buonomano, Annamaria & Giuzio, Giovanni Francesco & Palombo, Adolfo, 2023. "Towards zero energy infrastructure buildings: optimal design of envelope and cooling system," Energy, Elsevier, vol. 279(C).
    18. Shaoxiong Li & Le Liu & Changhai Peng, 2020. "A Review of Performance-Oriented Architectural Design and Optimization in the Context of Sustainability: Dividends and Challenges," Sustainability, MDPI, vol. 12(4), pages 1-36, February.
    19. Tajda Potrč Obrecht & Martin Röck & Endrit Hoxha & Alexander Passer, 2020. "BIM and LCA Integration: A Systematic Literature Review," Sustainability, MDPI, vol. 12(14), pages 1-19, July.
    20. Razmi, Afshin & Rahbar, Morteza & Bemanian, Mohammadreza, 2022. "PCA-ANN integrated NSGA-III framework for dormitory building design optimization: Energy efficiency, daylight, and thermal comfort," Applied Energy, Elsevier, vol. 305(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:15:y:2022:i:9:p:3412-:d:810227. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.